AI Engineer specializing in Neural Scene Reconstruction for autonomous driving simulation environments.
Responsibilities
Develop and improve neural scene reconstruction models using 3DGS, NeRF, and other learned 3D representations to reconstruct realistic driving environments.
Implement dynamic scene reconstruction techniques, modeling static environments and moving traffic agents while handling occlusions, incomplete observations, and challenging environmental conditions.
Develop neural rendering and novel-view synthesis methods to generate realistic camera observations from reconstructed 3D scenes.
Contribute to multimodal sensor rendering, including camera, LiDAR, and radar simulation, to support realistic virtual testing environments.
Build scalable reconstruction and rendering pipelines for efficient experimentation and large-scale processing of real-world driving datasets.
Requirements
Bachelor's or Master's degree in Computer Science, Computer Vision, Robotics, Electrical Engineering, or a related discipline, or equivalent practical experience.
Develop scalable data pipelines and automated workflows that transform raw sensor data and external map sources into reliable, high-quality maps for autonomous driving.
Responsibilities
Develop and maintain automated map production pipelines, covering data ingestion, alignment, map conflation, format conversion, validation, packaging, and release.
Build automated map validation tools to detect geometric inconsistencies, topology errors, connectivity issues, and missing or incorrect map attributes.
Develop scalable map storage and retrieval services, including map indexing, tile serving, lane-level queries, and APIs for autonomous driving applications.
Implement map format conversion and export tools, supporting industry-standard formats such as OpenDRIVE and Lanelet2 for simulation, planning, and evaluation.
Build robust data processing workflows for integrating vehicle sensor logs, HD maps, and third-party geospatial datasets.
Requirements
Bachelor's degree in Computer Science, Robotics, Software Engineering, or a related discipline
Master's degree in Computer Science, Robotics, Software Engineering, or a related discipline
Drive high data integrity by establishing robust validation rules, governance standards, and automated system checks
Perform deep‑dive analysis on large and complex datasets to uncover customer insights, behavioral trends, and strategic business opportunities
Create compelling dashboards and data visualizations that translate complex findings into clear, actionable insights for both technical and non‑technical stakeholders
Develop advanced SQL queries, scalable data models, and end‑to‑end analytics solutions that directly support evolving business needs
Design, streamline, and optimize reporting frameworks, automated processes, and analytical workflows to enhance efficiency and decision‑making
Support the initiative by conducting literature reviews, managing data, recruiting participants, scheduling and conducting interviews and surveys, and translating documents between Vietnamese and English.
Compensation
Competitive remuneration VND package for Vietnamese candidates.
Responsibilities
Conduct fieldwork and research activities under the supervision of the Line Manager
Conduct, record, and transcribe interviews in English or Vietnamese, including translation when necessary
Assist with the design of data collection tools, scientific tests, and interview protocols
Ensure that data collection, storage, and preliminary analysis follow required research protocols and ethical standards
Carry out qualitative and quantitative data analysis using appropriate tools and methods
Requirements
Postgraduate degree (Master’s) in Natural Science, Social Science, Economics, Business, or a related Engineering field
Senior Python Engineer responsible for designing, building, and scaling backend systems that power AI across the platform.
Locations (2)
Hanoi, Hanoi, Vietnam
Ho Chi Minh City, Ho Chi Minh City (HCMC), Vietnam
Responsibilities
Design, implement, and maintain robust Python/FastAPI microservices and backend systems that integrate LLMs and generative AI capabilities directly into live workflows.
Build automated pipelines and tooling to continuously measure, evaluate, and improve LLM output accuracy, consistency, latency, and safety.
Develop internal libraries, abstractions, and standardized patterns that empower engineering squads to ship AI features quickly and reliably.
Optimize AI services and inference pipelines for throughput, latency, token economics, caching, and high availability.
Partner with the CTO and technical leads to evaluate emerging AI technologies, architect retrieval-augmented generation (RAG) pipelines, and design vector search infrastructure.
The Centric PXM Technical Consultant is the technical delivery authority for Centric PXM in APAC. The role ensures that every Centric PXM implementation – whether delivered directly by Centric, by certified SI/reseller partners, or with subcontracted resources – goes live on time, to Centric quality standards, and becomes a referenceable customer. The role bridges Sales, Partners, Subcontractors, and Customers: shaping what is sold, governing how it is built, and owning what is delivered.
Responsibilities
Act as Project Manager and technical lead for Centric PXM projects contracted directly with customers
Serve as Centric’s technical authority for SI and reseller partners in APAC
Plan, assign, and supervise subcontracted consultants and developers
Own the quality management framework for Centric PXM projects in APAC
Support Sales with discovery workshops, solution architecture, demonstrations and proofs of concept
Requirements
Bachelor’s or Master’s degree, preferably in Computer Science, MIS, Engineering, or similar
Own the AWS infrastructure for all platform environments (dev, staging, production and DR) through Terraform, with every change going through PR review and a pipeline plan.
Locations (2)
Danang, Vietnam
Hanoi, Hanoi, Vietnam
Responsibilities
Operate and upgrade the EKS clusters
Maintain the Bitbucket Pipelines and Helm GitOps flow
Run and test the disaster recovery setup
Keep the security baseline green
Run observability and alerting with Prometheus, Grafana, Loki and CloudWatch